AI tools are showing up everywhere in law practice—drafting emails, summarizing discovery, researching case law, even suggesting arguments. Along with the productivity boost comes a nervous question many lawyers have been asking in real-world threads on Reddit and other legal forums: “If the AI gets it wrong and I get sued, is my malpractice carrier going to cover me?”
The practical answer is that coverage usually turns less on whether AI was involved and more on what went wrong, what you did (or didn’t do) to supervise it, and what your policy excludes. Below is a plain-English map of how AI mistakes can turn into claims and what most legal malpractice policies typically cover—and don’t.
When AI Errors Become Malpractice Claims for Lawyers
AI “hallucinations” are the headline risk, and they map neatly onto classic malpractice theories. Lawyers in online discussions often describe scenarios like: an AI-generated memo cites cases that don’t exist; a drafted motion misstates the holding; a brief contains invented quotations; or a contract clause is copied from an AI suggestion that is subtly wrong for the jurisdiction. When those errors are filed with a court, relied on in a transaction, or used to advise a client, the claim isn’t “AI malpractice”—it’s still alleged negligence, failure to meet the standard of care, or breach of fiduciary duty. Courts and bars have been clear that the lawyer remains responsible for work product and supervision, even if software produced the first draft.
A second cluster of risks is workflow-driven: missed deadlines, wrong filings, and “silent” research gaps. Forum posts from practicing attorneys frequently focus on practical misfires—calendar entries created from an AI transcript that misreads the hearing date, auto-summarization that omits a key limitation period, or document review models that fail to flag a hot document because it was poorly prompted or poorly trained. If a statute of limitations is missed, or a dispositive argument never gets raised, the client’s damages can be real and straightforward.
That kind of loss is the same kind carriers have always seen (docketing errors, oversight, failure to investigate), just with a new tool in the chain.
The third category is confidentiality and data handling—often discussed online with more anxiety than any other AI issue. Lawyers worry about pasting privileged facts into a public-facing model, uploading client documents to a vendor without adequate safeguards, or enabling plugins that send data to third parties.
These can become malpractice claims if the disclosure harms the client (e.g., waiver of privilege, strategic disadvantage, regulatory trouble). They can also become disciplinary problems and potential cyber incidents even without a traditional malpractice damages theory—meaning you might face multiple parallel issues: a malpractice demand, a bar complaint, and incident response costs.
What Malpractice Policies Cover (and Often Exclude)
Most legal malpractice policies are professional liability policies designed to cover claims alleging negligence in the rendering of legal services. In typical forms, if an AI-driven mistake results in an allegation that you failed to exercise reasonable care—say, you relied on a bogus citation and the client lost a motion—you may have a covered “error or omission,” provided the claim falls within the insuring agreement, happened after the retroactive date, and is reported correctly during the policy period.
In many carriers’ eyes, AI is just another tool like Westlaw, a paralegal draft, a template, or outsourced research: coverage tends to hinge on whether it was a professional services mistake, not whether the mistake came from silicon or a human. That said, insurers will still scrutinize supervision, reasonableness, and whether you followed your own internal review steps.
Where lawyers on forums often get surprised is the boundary between malpractice coverage and cyber/privacy coverage. A traditional legal malpractice policy may provide some limited coverage for claims alleging breach of confidentiality as part of legal services, but it often does not pay for many first-party breach costs (forensics, notification, credit monitoring, extortion payments, business interruption) unless you have a separate cyber policy or an endorsement.
If an AI tool leaks client data, you could face (1) a malpractice claim by the client, (2) regulatory inquiries, and (3) incident response expenses. Your malpractice policy may help with the claim (defense/indemnity) depending on allegations, but still leave you exposed on the operational breach-response bill—something that comes up repeatedly in practitioner discussions comparing “malpractice vs. cyber” insurance.
Common exclusions and conditions are where AI use can create coverage fights. Many policies exclude intentional, fraudulent, or knowingly wrongful acts; if someone knowingly files fabricated citations, the carrier may defend under a reservation of rights but later argue the conduct was intentional. Some policies have exclusions related to fines, penalties, sanctions, and punitive damages—so if a court sanctions you for an AI-citation debacle, that sanction may not be covered even if the underlying malpractice claim is.
Another frequent issue is “failure to supervise” or “outsourcing/vendor” problems: not because the policy explicitly excludes AI, but because inadequate controls can make the claim harder to defend and can also trigger misrepresentation issues if the application asked about tech controls, use of vendors, or risk management practices. The practical takeaway many lawyers share: treat AI like any other delegated work—document review, verify sources, keep prompts and outputs in the file when appropriate, and be careful about what data you feed into third-party systems.
Malpractice insurance can cover AI-related mistakes, but it rarely covers them because they are AI mistakes—it covers (or excludes) them based on familiar concepts: negligent legal services vs. cyber incidents, accidental errors vs. intentional misconduct, and covered damages vs. sanctions and penalties.
If you’re using AI in client work, the most helpful step is to read your specific policy’s insuring agreement, definitions of “professional services,” and exclusions—then talk to your broker about whether you need cyber coverage or endorsements for privacy and incident response. AI doesn’t remove your duty to supervise and verify; it just changes where the weak links are, and insurance tends to follow those fault lines.